Research on Real-time Pedestrian Detection Algorithm based on Ghostnet and ECA
A real-time pedestrian detection algorithm based on GhostNet and ECA--Little-YOLOv4 neural network algorithm is proposed.Little-YOLOv4 neural network algorithm uses Mosaic data enhancement method in the image preprocessing stage to enrich the detection data set and improve the robustness of the model.Lightweight GhostNet is used to replace CSPDarkNet53 feature extraction network,which reduces the computation and parameters of the model;Introducing ECANet into the network can effectively capture cross-channel interaction,and only a few parameters are involved to achieve good results.The experimental results show that the Little-YOLOv4 neural network algorithm has a certain improvement in accuracy and speed.
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